Empirical and modeling evidence of the long-range atmospheric transport of decabromodiphenyl ether

Understanding of the long-range atmospheric transport (LRT) behavior of decabromodiphenyl ether (BDE-209) is still limited. Most existing model-based approaches to assessing an organic chemical's potential for LRT have assumed invariant environmental conditions, even though many factors impacting on the atmospheric residence time are known to vary considerably over a variety of time scales. Model estimates of LRT also suffer from limited evaluation against observational evidence. Such evidence was sought from dated sediment cores taken from lakes along a latitudinal transect in North America. BDE-209 was generally detected only in recent sediment horizons, and sedimentation fluxes were found to decline exponentially with latitude. The empirical half-distance (EHD) for BDE-209 derived from surface flux data is approximately half that of the T PCBs. A dynamic multimedia fate and transport model provides further insight into the temporal variability of processes that control LRT for BDE-209 and PCBs. The variability of precipitation, and in particular, the occurrence of time periods without precipitation coinciding with strong winds, influences the LRT potential of chemicals that combine a sufficiently long atmospheric half-life with very low volatility. Likewise, the forest filter effect may be important for a wider range of chemicals than believed previously, because models assuming constant precipitation fail to account for the impact of differences in dry deposition on days without rain. Chemicals that are both sorbed to particles and potentially persistent in the atmosphere, such as BDE-209, may have a larger potential for LRT than anticipated on the basis of earlier model evaluations. Still, the EHDs illustrate that the model seems to underestimate atmospheric loss processes of potential significance to BDE-209, illustrating the need to critically compare predictions of LRT against observations. Processes that need to be understood better in order to improve predictions of LRT for BDE-209 include particle dry deposition, precipitation scavenging, and photolysis in the sorbed state.